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Covalent Inhibition Kinetics24 Likelihood profile method: Computational algorithm 1.Perform nonlinear least-squares fit with the full set of model parameters. 2.Progressively increase a parameter of interest, P, away from its best-fit value. From now on keep P fixed in the fitting model. 3.At each step optimize the remaining model parameters. 4.Continue stepping with P until the sum of squares reaches a critical level. 5.This critical increase marks the upper end of the confidence interval for P. 6.Go back to step #2 and progressively decrease P, to find the lower end of the confidence interval. Watts, D.G. (1994) "Parameter estimates from nonlinear models“ Methods in Enzymology, vol. 240, pp

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Covalent Inhibition Kinetics39 Substrate mechanism – Michaelis-Menten ASSUMING THAT ATP COMPETITION CAN BE EXPRESSED THROUGH “APPARENT” K i “S” is the peptide substrate All inhibitors are ATP-competitive Therefore they are “S”-noncompetitive